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Saram ConsultingThoughts and strategies on the intersection of Biotech, Artificial Intelligence, and Regulatory Compliance.
Computer System Validation is 60-70% documentation, traceability, and structured analysis. Here is exactly what AI agents can automate right now — organized by validation lifecycle phase, with consensus strength and realistic time savings.
Read Article →Most AI agent evaluations for pharma QA measure the wrong things. Here is the evaluation framework that actually predicts whether an agent will survive an FDA inspection — built from the convergence of every serious analysis on this problem.
Read Article →Every unique prompt variant is a cache miss, and frontier models charge premium prices per token. Here's the layered architecture — from free application caches to DSPy-distilled local models — that eliminates most of those calls before they happen.
Read Article →DSPy doesn't make small models smarter. It systematically discovers the optimal interface between a task and a model. Here's the exact mechanism — bootstrapping, Bayesian instruction search, reflective evolution, and weight-level distillation — that makes it happen.
Read Article →Life science quality teams want AI. Regulators demand determinism. The AI Harness resolves the tension — a governed orchestration layer that makes every LLM output traceable, auditable, and defensible under GxP. Here's the full architecture.
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